Differences in virus and immune dynamics for SARS-CoV-2 Delta and Omicron infections by age and vaccination histories

Vaccination against COVID-19 was integral to controlling the pandemic that persisted with the continuous emergence of SARS-CoV-2 variants. Using a mathematical model describing SARS-CoV-2 within-host infection dynamics, we estimate differences in virus and immunity due to factors of infecting variant, age, and vaccination history (vaccination brand, number of doses and time since vaccination). We fit our model in a Bayesian framework to upper respiratory tract viral load measurements obtained from cases of Delta and Omicron infections in Singapore, of whom the majority only had one nasopharyngeal swab measurement. With this dataset, we are able to recreate similar trends in URT virus dynamics observed in past within-host modelling studies fitted to longitudinal patient data. We found that Omicron had higher R0,within values than Delta, indicating greater initial cell-to-cell spread of infection within the host. Moreover, heterogeneities in infection dynamics across patient subgroups could be recreated by fitting immunity-related parameters as vaccination history-specific, with or without age modification. Our model results are consistent with the notion of immunosenescence in SARS-CoV-2 infection in elderly individuals, and the issue of waning immunity with increased time since last vaccination. Lastly, vaccination was not found to subdue virus dynamics in Omicron infections as well as it had for Delta infections. This study provides insight into the influence of vaccine-elicited immunity on SARS-CoV-2 within-host dynamics, and the interplay between age and vaccination history. Furthermore, it demonstrates the need to disentangle host factors and changes in pathogen to discern factors influencing virus dynamics. Finally, this work demonstrates a way forward in the study of within-host virus dynamics, by use of viral load datasets including a large number of patients without repeated measurements. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-024-09572-x.


Equations S1
Model in which the main mechanism immunity controls infection is via clearance of free virus.In this model, free virus is cleared by immunity via a mass action process, and is represented by γ parameter.For this model, we estimated infection rate of target cells (b), natural clearance of infected cells (d), rate of clearance of free virus by immunity (g) and growth rate of immunity (w).The natural clearance of virus (c) was fixed at 1.0 /day for this model.

Figure S1 .
Figure S1.COVID-19 case count in Singapore reported to WHO from April 2021 to June 2022, and the number of swabs taken each day in the unfiltered and filtered datasets.COVID-19 case count is represented by the black line, following the primary axis.The number of swabs taken each day is represented by the yellow bars, while the data subset used for our study is represented by the blue bars.Both colours of bar follow the secondary axis.

Figure S2 .
Figure S2.Plots of viral load data over day of symptoms from swabbed individuals included in this study, by vaccine group and age subgroup, with coloured points representing the time since last vaccine dose subgrouping.(a) Delta infections, (b) Omicron infections.Delta infections are defined as cases with date of symptom onset between 1 June 2021 to 30 November 2021, Omicron infections are defined as 1 January 2022 to 18 February 2022.
Fig S6.Observed viral load and output from Model Type 2 fit, the selected model which fits infected cell clearance rate by immunity (γ) as vaccination history-specific, and growth rate of immunity (ω) as age-modified, vaccination history-specific.Grey dots represent observed viral loads.Black lines are median posterior for virus dynamics.Green lines are samples from the posterior of uninfected target cell dynamics.Purple lines are samples from the posterior of immune response dynamics.Red lines are samples from the posterior of virus dynamics.(a) Delta infections, (b) Omicron infections.

Fig S7 .
Fig S7.Viral load outputs from model fit to dataset which only includes the first swab taken per patient.Viral loads are stratified by age group, vaccine brand and number of doses received.mRNA-based vaccines are represented by the following colour gradients; yellow to orange for Pfizer-only groups, light green to emerald for Moderna-based groups, lilac to dark purple for PPM, and light blue to navy for MMP.Non-mRNA-based vaccines are represented as follows; light blue to navy for Sinopharm groups, and pink to maroon for Sinovac.Colour gradient scales with increasing time since last vaccinated.Unvaccinated groups are shown in black, and plotted as a reference.(a) Delta infections (b) Omicron infections.

Fig S12 .
Fig S12.Observed viral load and output from model fit to dataset which only includes patients with one swab for Delta and Omicron infections.Grey dots represent observed viral loads.Black lines are median posterior for virus dynamics.Green lines are samples from the posterior of uninfected target cell dynamics.Purple lines are samples from the posterior of immune response dynamics.Red lines are samples from the posterior of virus dynamics.(a) Delta infections, (b) Omicron infections.